Reverse engineering morphogenesis

在生物体的发育过程中，组织的形状和结构是如何产生的？这个过程被称为形态发生，涉及形成组织内的细胞以协调的方式移动和重新配置自己。这种编排是自我组织的。没有中央列车长。相反，形态发生依赖于组织中各个细胞之间的相互作用和交流。理解这是如何起作用的仍然是科学的巨大挑战之一。复杂的组织形状是如何从单个细胞之间的相互作用中产生的？如何解释形态发生的可靠性？机制和基因活性的变化如何相互作用？自组织需要一个初始事件，当特定基因成为一种新的细胞类型(它们分化)时，该事件会导致细胞亚群中特定基因的活性发生变化。这会导致这些细胞的力学发生变化，并促使组织的形状发生变化。然后，该过程反复进行。随着不同类型的细胞之间形成新的接触，随着一些细胞彼此失去联系，随着新的信号和机械相互作用的产生，进一步的组织发生。因此，理解形状获得处于物理学和生物学之间的界面，因为它涉及力学和基因表达的循环变化，这些循环在多个长度和时间尺度上反馈。挑战是：i)我们不知道力学和基因表达的变化在何时何地发生；ii)我们不知道单个细胞的力学变化是如何加在一起改变组织的形状的；iii)反过来，我们不知道细胞力学和形状的变化如何影响基因表达，以建立下一轮形状变化。我们的愿景是将物理学和生物学的观点结合起来，以了解基因表达和机械变化的循环如何在几天的时间内在组织和器官中产生复杂的形状。我们建议在组织发育的实验模型中确定细胞分化和细胞尺度的机械变化如何相互作用来控制形状的获得，这种模型被称为有机体。这些细胞是在特定条件下从培养皿中培养的胚胎干细胞体外产生的。这是一个很有吸引力的系统，因为有机化合物可以重复产生特定的细胞类型并经历独特的形态发生，但仍然足够简单，以高空间和时间精度探索细胞形态、力学、分化和基因表达。在这个项目中，我们将使用一系列实验分析来表征组织形态、细胞形态、细胞分化和有机体内的基因表达，并确定力学、细胞黏附和基因表达如何相互反馈。使用这些数据将确定将分化与力学和力学与细胞类型联系起来的规则。在此基础上，我们将开发基于实验观测的计算机模型。我们将使用这些模型来确定组织形态发生的基本原理。有了这些模型，我们将对有机体形状的演变做出预测，以响应特定的干预措施，并进行实验测试。我们的团队是回答这些问题的理想人选，因为我们在脊髓有机体和发育生物学(James Briscoe)、细胞和组织力学(Guillaume Charras)以及定量成像、建模和理论(Tim Saunders)方面的综合专业知识。除了基础科学，在简化的模型系统中开发组织形状获取的多尺度模拟将为理解由多种和不断演变的细胞类型组成的复杂组织提供基础。这将在疾病建模、再生医学、合成生物学和组织工程中得到应用。

How does the shape and structure of a tissue arise during the development of an organism? This process, which is termed morphogenesis, involves the cells within a forming tissue moving and reconfiguring themselves in a coordinated manner. This choreography is self-organised. There is no central conductor. Instead, the morphogenesis depends on interactions and communication between the individual cells in the tissue. Understanding how this works remains one of the great challenges of science. How do complex tissue shapes arise just from interactions between individual cells? What explains the reliability of morphogenesis? How do mechanics and changes in gene activity interact with one another?Self-organisation necessitates an initial event that causes changes in the activity of specific genes in a subpopulation of the cells as they become a new cell type (they differentiate). This results in changes in the mechanics of these cells and precipitates a change in the shape of the tissue. The process then iterates. As new contacts form between cells of different type, as some cells lose contact with each other, and as new signals and mechanical interactions are produced, further rounds of organisation take place. Thus, understanding shape acquisition lies at the interface between physics and biology as it involves cycles of changes in mechanics and gene expression that feed back across multiple length and time scales.The challenges are: i) we do not know where and when changes in mechanics and gene expression occur; ii) we do not know how changes in the mechanics of individual cells add up to change the shape of the tissue; and iii) in turn, we do not know how changes in cell mechanics and shape influence gene expression to set up the next round of shape change. Our vision is to integrate physics and biological perspectives to develop an understanding of how cycles of gene expression and mechanical changes give rise to complex shape in tissues and organs over a duration of several days. We propose to determine how cell differentiation and cellular-scale mechanical changes interplay to control the acquisition of shape in an experimental model of tissue development, known as organoids. These are generated in vitro from embryonic stem cells grown in Petri dishes in defined conditions. This is an attractive system as organoids reproducibly produce defined cell types and undergo characteristic morphogenesis but remain sufficiently simple to explore cell morphology, mechanics, differentiation and gene expression with high spatial and temporal accuracy. In this project, we will use a combination of experimental assays to characterise tissue shape, cell morphology, cell differentiation, and gene expression in organoids and determine how mechanics, cell adhesion, and gene expression feed back onto one another. Using these data will determine rules linking differentiation to mechanics and mechanics to cell type. From this, we will develop computer models based on the experimental observations. We will use the models to identify underlying principles of tissue morphogenesis. And with these models, we will make predictions of organoid shape evolution in response to specific interventions and test these experimentally. Our team is ideally placed to answer these questions because of our combined expertise in spinal cord organoids and developmental biology (James Briscoe), cell and tissue mechanics (Guillaume Charras), and quantitative imaging, modelling, and theory (Tim Saunders). Beyond fundamental science, developing multi-scale simulations of tissue shape acquisition in a simplified model system will provide a foundation for understanding complex tissues comprising multiple and evolving cell types. This will have applications in disease modelling, regenerative medicine, synthetic biology and tissue engineering.